1. Field of the Invention
The present invention generally relates to quantizing apparatus and, more particularly, is directed to a neural network quantizer which quantizes an analog signal by using a multi-level neural network.
2. Description of the Prior Art
In the prior art, an analog signal may be quantized (digitized) by a quantization method which utilizes analog-to-digital (A/D) conversion. According to this quantization method utilizing A/D conversion, an input signal is sampled at an arbitrary moment, the sampled values obtained at every moment are classified in response to amplitudes and values corresponding to these classes are output.
This conventional method has an advantage, in that, the apparatus associated therewith has a relatively simple arrangement since the values are determined at every moment. On the other hand, characteristics in the frequency region are not at all considered. Such characteristics may include the noises generated by the quantization which are concentrated at a specific frequency. In the conventional apparatus, in order to make the concentrated noises appear inconspicuous white noise is added.
In accordance with the above-described conventional quantization method using A/D conversion, the signals lying in a frequency range from a DC component to 1/2 of the sampling frequency are uniformly weighted and then converted as a result, when a desired signal exists only in one frequency band, the encoding efficiency is not satisfactory.